Competencies and objectives
- Course context for academic year 2017-18
- Course content (verified by ANECA in official undergraduate and Master’s degrees)
- Learning outcomes (Training objectives)
- Specific objectives stated by the academic staff for academic year 2017-18
Course context for academic year 2017-18
Esta asignatura se ubica en el módulo Avanzado y dentro de él en la materia "Matemáticas Aplicadas a las Ciencias Sociales". Dicha materia incluye además las asignaturas: "Teoría de Juegos", “ Decisiones Colectivas” y “Economia de la Información y de la Incertidumbre”. La asignatura pretende enseñar al alumno a construir modelos de series temporales para explicar la evolución histórica de una variable a lo largo del tiempo y predecir sus valores futuros. En concreto, trataremos los problemas de identificación, estimación, selección, validación y predicción de modelos autorregresivos (AR), media móvil (MA), autorregresivos de media móvil (ARMA), y de modelos autorregresivos integrados de media móvil (ARIMA). La exposición de la teoría se completará con clases de prácticas de problemas y con clase de prácticas con ordenador. En estas últimas, el alumno aprenderá el manejo del software R para la aplicación de los métodos estudiados en teoría a series reales. Los conocimientos previos requeridos para cursar con éxito la asignatura son los fundamentos de probabilidad e inferencia que se adquieren en las asignaturas de “Introducción a la Estadística”, “Probabilidad”, e “Inferencia Estadística”. Es aconsejable, aunque no imprescindible, un buen conocimiento de los métodos de regresión lineal (que se imparten en la asignatura de “Análisis de Datos I”).
Course content (verified by ANECA in official undergraduate and Master’s degrees)
Specific Competences (CE)
- CE10 : Communicate, both orally and in writing, mathematical knowledge, procedures, results and ideas.
- CE11 : Ability to solve academic, technical, financial and social problems using mathematical methods.
- CE12 : Ability to work in a team, providing mathematical models adapted to the needs of the group.
- CE15 : Recognise and analyse new problems and prepare strategies to resolve them.
- CE5 : Propose, analyse, validate and interpret models of simple real-life situations, using the most appropriate mathematical tools for the purpose.
- CE6 : Solve mathematical problems using basic calculus skills and other techniques, planning their resolution according to the tools available and any time and resource restriction.
- CE7 : Use computer applications for statistical analysis, numerical calculus and symbolic calculus, graphic visualisation and others to experiment in Mathematics and solve problems.
- CE9 : Use bibliographic search tools for Mathematics.
Specific Generic UA Competences
- CGUA1 : Understand scientific English.
- CGUA2 : Possess computer knowledge related to the field of study.
- CGUA3 : Acquire or posses basic ICT (Information and Communication technology) skills and manage the information obtained appropriately.
Generic Degree Course Competences
- CG1 : Develop the capacity for analysis, synthesis and critical reasoning.
- CG2 : Show the ability for effective and efficient direction/management: entrepreneurial spirit, creativity, organisation, planning, control, decision making and negotiation.
- CG3 : Resolve problems effectively.
- CG4 : Show ability for teamwork.
- CG5 : Commitment to ethics, the values of equality and social responsibility as a citizen and as a professional.
- CG6 : Learn autonomously.
- CG7 : Show the ability to adapt to new situations.
- CG9 : Demonstrate the ability to transmit information, ideas, problems and solutions to both specialist and non-specialist audiences.
Learning outcomes (Training objectives)
No data
Specific objectives stated by the academic staff for academic year 2017-18
No data
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